公开(公告)号：US20250078531A1

公开(公告)日：2025-03-06

申请号：US18242928

申请日：2023-09-06

Applicant: Waymo LLC

Inventor： Hang Yan ,  Zhengyu Zhang ,  Yan Wang ,  Jingxiao Zheng ,  Dmitry Kalenichenko ,  Vasiliy Igorevich Karasev ,  Alper Ayvaci ,  Xu Chen

IPC: G06V20/56 ,  B60W60/00 ,  G01S13/89 ,  G06V10/764 ,  G06V10/80

Abstract: A method includes obtaining, by a processing device, input data derived from a set of sensors of an autonomous vehicle (AV), generating, by the processing device using a set of lane detection classifier heads, at least one heatmap based on a fused bird's eye view (BEV) feature generated from the input data, obtaining, by the processing device, a set of polylines using the at least one heatmap, wherein each polyline of the set of polylines corresponds to a respective track of a first set of tracks for a first frame, and generating, by the processing device, a second set of tracks for a second frame after the first frame by using a statistical filter based on a set of extrapolated tracks for the second frame and a set of track measurements for the second frame, wherein each track measurement of the set of track measurements corresponds to a respective updated polyline obtained for the second frame.

公开(公告)号：US20250022143A1

公开(公告)日：2025-01-16

申请号：US18221577

申请日：2023-07-13

Applicant: Waymo LLC

Inventor： Qinru Li ,  Longlong Jing ,  Ruichi Yu ,  Xu Chen ,  Shiwei Sheng

IPC: G06T7/20 ,  G01S17/89 ,  G05D1/02 ,  G06V10/25 ,  G06V10/44 ,  G06V20/56

Abstract: The described aspects and implementations enable efficient and seamless tracking of objects in vehicle environments using different sensing modalities across a wide range of distances. A perception system of a vehicle deploys an object tracking pipeline with a plurality of models that include a camera model trained to perform, using camera images, object tracking at distances exceeding a lidar sensing range, a lidar model trained to perform, using lidar images, object tracking at distances within the lidar sensing range, and a camera-lidar model trained to transfer, using the camera images and the lidar images, object tracking from the camera model to the lidar model.

公开(公告)号：US11733369B2

公开(公告)日：2023-08-22

申请号：US17173818

申请日：2021-02-11

Applicant: Waymo LLC

Inventor： Xu Chen ,  Hang Zhao ,  Ruichi Yu

IPC: G01S13/86 ,  G01S13/931 ,  G01S13/89 ,  G06T7/70 ,  B60W30/08 ,  G01S7/41

CPC classification number: G01S13/867 ,  B60W30/08 ,  G01S7/417 ,  G01S13/86 ,  G01S13/89 ,  G01S13/931 ,  G06T7/70 ,  B60W2420/42 ,  B60W2420/52 ,  B60W2554/00 ,  B60W2754/10 ,  G01S2013/93271 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/20084 ,  G06T2207/30252

Abstract: Example embodiments relate to techniques for three dimensional (3D) object detection and localization. A computing system may cause a radar unit to transmit radar signals and receive radar reflections relative to an environment of a vehicle. Based on the radar reflections, the computing system may determine a heading and a range for a nearby object. The computing system may also receive an image depicting a portion of the environment that includes the object from a vehicle camera and remove peripheral areas of the image to generate an image patch that focuses upon the object based on the heading and the range for the object. The image patch and the heading and the range for the object can be provided as inputs into a neural network that provides output parameters corresponding to the object, which can be used to control the vehicle.

公开(公告)号：US20230046274A1

公开(公告)日：2023-02-16

申请号：US17445129

申请日：2021-08-16

Applicant: Waymo LLC

Inventor： Xu Chen ,  Nichola Abdo ,  Ruichi Yu ,  Chang Gao

IPC: G01S7/41 ,  G06K9/00 ,  G06K9/62 ,  G06T7/20 ,  G01S13/86 ,  G01S13/931 ,  B60W60/00

Abstract: The described aspects and implementations enable fast and accurate verification of radar detection of objects in autonomous vehicle (AV) applications using combined processing of radar data and camera images. In one implementation, disclosed is a method and a system to perform the method that includes obtaining a radar data characterizing intensity of radar reflections from an environment of the AV, identifying, based on the radar data, a candidate object, obtaining a camera image depicting a region where the candidate object is located, and processing the radar data and the camera image using one or more machine-learning models to obtain a classification measure representing a likelihood that the candidate object is a real object.